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  • SyncSolutions.ai
  • New York City
  • 01:21 (UTC -04:00)

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siroxou/README.md

Hey, I'm Siro πŸ‘‹

Co-Founder @ Syncsolutions.ai Β· AI/ML Engineer in progress
Building AI automation systems out of New York City.


πŸš€ What I'm Building

πŸ”¬ Enterprise Agentic RAG β€” why it matters

Most RAG demos answer questions over a pile of PDFs. Enterprises can't ship that β€” retrieval leaks data. This project enforces access at the database level via Postgres Row-Level Security, so a buggy app query physically cannot return a chunk the caller isn't cleared for. Paired with a LangGraph supervisor, layered ShieldGemma guardrails, and a LoRA-fine-tuned Gemma 4 running fully local on Apple Silicon.

Stack: FastAPI Β· LangGraph Β· pgvector + RLS Β· BGE-M3 Β· MLX / Ollama Β· vLLM (Modal) Β· ShieldGemma Β· LangFuse Β· Next.js Β· Docker Β· OpenRouter Β· Tavily


πŸ›  Stack

Languages
Python TypeScript JavaScript

ML / AI Frameworks
PyTorch HuggingFace LangChain LangGraph scikit-learn MLX

LLMs & Inference
Ollama vLLM Anthropic OpenAI NVIDIA OpenRouter

Web & Backend
Next.js React FastAPI Supabase PostgreSQL

Cloud & Infra
Google Cloud Azure AWS Modal Docker Vercel

Observability & Tools
LangFuse Claude Code n8n Playwright Jupyter


πŸ“œ Certifications

  • βœ… NVIDIA NCA-GENL β€” Certified Associate, Generative AI LLMs (2026)
  • πŸ”„ NVIDIA NCP β€” Certified Professional, Generative AI LLMs (in progress)
  • πŸ”„ Google Cloud PMLE β€” Professional ML Engineer (in progress)
  • πŸ”„ Azure AI-102 β€” Designing & Implementing AI Solutions (in progress)
  • πŸ”„ AWS Certified ML Specialty (in progress)
  • πŸ”„ TensorFlow Developer Certificate β€” Google (in progress)
  • πŸ”„ DeepLearning.AI MLOps Specialization (in progress)
  • πŸ”„ DeepLearning.AI LLMOps (in progress)

βš™οΈ Setup

  • 🍎 Apple M5 Max Β· 64GB Β· MacBook Pro 16" (I much prefer this, apple on top)
  • πŸ–₯️ RTX 5090 Β· i7-14700KF Β· 256GB DDR5 (local training + Ollama inference)

πŸ“« Connect

LinkedIn Website

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  1. advanced-rag advanced-rag Public

    Enterprise agentic RAG: multi-agent, context-aware retrieval with document-level RBAC (Postgres RLS), guardrails, and a local Gemma 4 + LoRA.

    Python 1

  2. local-language-machine local-language-machine Public

    All-in-one, fully offline local AI coding β€” self-contained inference, zero external services.

    TypeScript 1

  3. lora-knowledge-injection lora-knowledge-injection Public

    Does LoRA fine-tuning inject new knowledge, and does model size change the answer? A controlled experiment across 3 model families and a 55x size range.

    TypeScript 1